WnCC - Seasons of Code
Seasons of Code is a programme launched by WnCC along the lines of the Google Summer of Code. It provides one with an opprtunity to learn and participate in a variety of interesting projects under the mentorship of the very best in our institute.
List of Running Projects
- Browser Based PDF manager
- Resume Script Generator
- Physicc : A Simple Physics Engine
- Image Colorization
- Language Model Based Syntax Autocompletion in a Text Editor
- Computer vision based web app
- Cribbit Cribbit (Open for PGs Only)
- Techster Texter
- Language Detection
- Book Tracker
- ResoBin - Not the bin we deserve but the bin we need!
- Agree to disagree
- Watson (World's smartest assistant in your pocket)
- Meta Learning - Learning to Learn
- Break free of the matrix, by building one!
- Procedurally Generated Infinite Open World
- Introduction to App Development
- PAC MAN
- Introduction to Web Development
- Goal ICPC
- Traffic congestion modelling and rendering
- Tools for Data Science
- Machine Learning Based Metropolitan Air Pollution Estimation
- Audio controlled drone
- NLPlay with Transformers
- DIY FaceApp
- A Deep Dive into CNNs
- Competitive Coding
- Snake AI
- Facial Recognition App
- Gaming meets AI !!!
- R(ea)L Trader
- Computational Geometry
- Deep reinforcement learning - 2048 AI
- Reinforcement Learning to Finance
- Developing Hybrid ANN-Statistical Model for Robust Stock Market Prediction
- Astronomical Data-modelling and Interpretation
- Visual Perception for Self Driving Cars
- Convolutional Neural Networks and Applications
- Quantum Computing Algorithms
- Algorithm Visualizer
- Anime Club IITB Website using Django
- Machine Learning in Browser
This project aims to automate the marking of the fiducials (bone based markers) in MRI/CT scan images.
Image-guided neurosurgery systems (IGNS) play an important role in intracranial surgery. These systems have a live CT/MRI scanning during surgeries to aid the doctor. During neuro-registration, bone based markers or fiducials are affixed to the skull before imaging so that they can calibrate the coordinate systems of the imaging device and the actual 3D World Coordinates. As of now, the actual Fiducials are tapped by instruments, and on the other hand they are MANUALLY marked out in the images obtained from the MRI/CT imaging. Automatic localization of these centers will help to reduce the human error in registration and speed up the registration process. In a nutshell, the task is to automatically locate these Fiducial markers from these images, so that they don’t have to be manually marked out by the doctor.
This project was a research challenge provided by scientists working in BARC (Bhabha Atomic Research Centre), during the Inter IIT Tech Meet, 2017 held at IITM. We came second, after developing an algorithm which worked quite well. We believe it can be further worked upon to work extremely well. This task is still open, and scientists in India are actively looking for a solution. Also, we found very little literature on this task, and aim to publish this work too.